About the role

Principal Data Engineer at Mashreq Bank designing and maintaining scalable data pipelines. Collaborating with teams to improve data models and ensure data quality and accessibility.

Responsibilities

Develops and maintains scalable data pipelines of batch and real-time to support continuing increases in data demands of volume and complexity.
Leading data engineering team and ensuring best practices and quality on the deliveries.
Designs and Develops Data domains across banking products and laying foundation for Data Mesh architecture.
Demonstrate deep knowledge and experience in databases, Datamart's, Data Modelling, Data Governance, Data Security, BI tools, ETL Solutions.
Data Orchestration and Data-Ops practices enabler for the team
Collaborates with analyst, data scientists and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
Writes unit/integration tests, contributes to engineering wiki, and documents work.
Experience in Automating Deployment, scheduling, monitoring, and management of datasets and pipelines
Understand business requirements and identify key performance indicators (KPIs) in Data Engineering.
Design data models to transform raw data into meaningful insights.
Ability to Debug Data issues in data platforms and Provide L2, L3 Production support as per SLA.

Principal Data engineer with a solid technical background and experience in data-intensive systems (> 15 years)
Strong experience in Big Data, Hadoop Ecosystem, Spark Streaming, Kafka, Python, SQL, Hive, NIFI, Airflow
Proficient with Azure Cloud services such as Azure Data Factory (ADF), Databricks, ADLS, Azure Synapse, Logic Apps, Azure Functions. Or similar data stack knowledge within Google/AWS cloud services
Proficiency in relational SQL, Graph and NoSQL databases.
Proficiency in Elastic Search and Couchbase databases
In-depth skills in developing and maintaining ETL/ELT data pipelines.
Experience in data modelling techniques such as Kimball star schema, 3NF, vault modelling etc.
Experience in workflow management tools such as Airflow, Oozie and CI/CD tools
Data streaming solution in Kafka or Confluent Kafka
Hands on experience in Google Big Query, Google Analytics & Clickstream Data Model
Reporting knowledge in Power BI, Tableau, Qlik etc.
Sound in Data Management Fundamentals and Data Architect, Modelling, Governance
Strong Domain Knowledge in Banking/Finance area like understanding of the various processes, products, and services within the banking industry, core functions, regulations, and operational aspects of banking institutions
Hands on knowledge in Hadoop and Azure/AWS cloud ecosystem and ETL jobs migration
Knowledge of Advance Analytics and AI tools

People management responsibilities encompass the tasks and activities involved in leading, guiding, and developing a team of individuals to achieve organizational goals effectively.
Setting clear performance expectations, conducting regular performance reviews, providing feedback, and offering guidance on areas of improvement.
Follow predefined processes and workflows to carry out specific tasks and activities accurately and in a timely manner.
Identify opportunities for process improvement and efficiency enhancement and provide feedback or suggestions to optimize workflows.
Analyze the needs, expectations, and concerns of each stakeholder. Assess their level of influence, interest, and potential power to affect the project's success.
Developing a comprehensive project plan that outlines the project scope, objectives, deliverables, timelines, resource requirements, and budget.